Systems Thinking
Scope
Covers
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Seeing the “whole system” behind a problem (actors, incentives, feedback loops, culture/rules)
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Anticipating second- and third-order effects (including time delays)
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Finding leverage points (small changes with outsized impact)
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Converting recurring pain into a reusable system (process, automation, or operating mechanism)
When to use
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“This is a complex ecosystem; we’re missing the bigger picture.”
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“What are the second-order effects if we do X?”
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“We keep solving symptoms—what’s the system causing this?”
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“Map the players + incentives and how they interact.”
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“We need to redesign a process/org without unintended consequences.”
When NOT to use
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The problem is simple/linear and mostly execution (use a project plan/timeline).
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You need primary user research or data you don’t have (do discovery first).
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You need deep quantitative forecasting/simulation (this skill produces a qualitative map + risks, not a full model).
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The decision is low-impact and fully reversible (don’t over-invest).
Inputs
Minimum required
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The focal decision or problem statement (1–2 sentences)
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Desired outcome + time horizon (default: 6–12 months)
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Known constraints/guardrails (trust, safety, compliance, budget, headcount)
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Known actors/stakeholders (teams, users, partners, regulators, vendors)
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What has been tried already (and what happened)
Missing-info strategy
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Ask up to 5 questions from references/INTAKE.md.
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If answers aren’t available, proceed with clearly labeled assumptions and provide 2–3 alternative system framings/boundaries.
Outputs (deliverables)
Produce a Systems Thinking Pack in Markdown (in-chat; or as files if requested) in this order:
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Context + System boundary (goal, scope, non-scope, time horizon)
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Actors & incentives map (players, goals, constraints, power, conflicts)
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System map (key variables + causal links) + feedback loops (reinforcing/balancing) + time delays
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Second-/third-order effects ledger for the top 1–3 decisions
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Leverage points + intervention plan (actions, owners, sequencing, guardrails)
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System-build opportunities (what to automate/standardize to reduce recurring pain)
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Risks / Open questions / Next steps (required)
Templates: references/TEMPLATES.md
Workflow (8 steps)
- Intake + pick the focal decision/problem
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Inputs: User context; use references/INTAKE.md.
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Actions: Restate the focal decision/problem, desired outcome, and time horizon; list constraints/guardrails.
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Outputs: Draft Context + System boundary.
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Checks: The problem is not a solution in disguise; scope and non-scope are explicit.
- Define the system boundary (what’s “in” vs “out”)
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Inputs: Problem statement + constraints.
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Actions: Choose a boundary that is useful (not everything). Name the primary outcome metric(s) and a few leading indicators.
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Outputs: Boundary statement + success measures.
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Checks: Boundary is tight enough to act on, but wide enough to include key externalities.
- Map actors + incentives (multi-agent reality)
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Inputs: Boundary + stakeholder list.
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Actions: Enumerate actors/players; capture incentives, constraints, power, and likely behaviors.
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Outputs: Actors & incentives map (table).
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Checks: Includes at least 1–2 “invisible” actors (e.g., policies, culture norms, platform constraints) if relevant.
- Build a simple system map (variables + causal links)
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Inputs: Actors map + known dynamics.
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Actions: List key variables; map causal links (“A increases B”, “C decreases D”); mark time delays.
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Outputs: System map (text/table) with 10–20 high-signal links.
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Checks: Links are directional and testable; avoids buzzwords (“alignment”, “quality”) without definition.
- Identify feedback loops + time delays
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Inputs: System map.
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Actions: Extract reinforcing and balancing loops; note where delays create overshoot/oscillation; flag common traps.
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Outputs: Feedback loops section (2–6 loops) + delays list.
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Checks: Each loop has a short “so what” describing the pattern it creates.
- Run second-/third-order effects on 1–3 candidate moves
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Inputs: Candidate decisions/actions.
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Actions: For each move, enumerate first-, second-, and third-order effects; include who wins/loses and what constraints tighten over time.
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Outputs: Second-/third-order effects ledger.
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Checks: Includes at least one unintended consequence + one mitigating action per move.
- Choose leverage points + design interventions (including “build a system”)
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Inputs: Loops + effects ledger.
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Actions: Identify leverage points (policy, incentives, information flows, tooling, process); propose interventions; include at least one system-build/automation opportunity for recurring pain.
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Outputs: Leverage points + intervention plan + System-build opportunities.
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Checks: Each intervention has an owner, a measurable leading indicator, and a guardrail.
- Quality gate + finalize pack
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Inputs: All draft sections.
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Actions: Run references/CHECKLISTS.md and score with references/RUBRIC.md. Add Risks / Open questions / Next steps.
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Outputs: Final Systems Thinking Pack.
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Checks: A reader can act without a live meeting; trade-offs and uncertainties are explicit.
Quality gate (required)
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Use references/CHECKLISTS.md and references/RUBRIC.md.
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Always include: Risks, Open questions, Next steps.
Examples
Example 1 (Org/process): “Our on-call load keeps rising and teams are burned out. Map the system and propose leverage points.”
Expected: an actors/incentives map (teams, incidents, incentives), feedback loops (firefighting loop), effects ledger for candidate changes, and an intervention plan with guardrails.
Example 2 (Product ecosystem): “We’re changing API pricing; what are the second-order effects across partners and customer segments?”
Expected: system boundary + actors map (customers/partners/internal), loops and delays, effects ledger, and a sequencing/mitigation plan.
Boundary example: “Write a status update about this week’s tasks.”
Response: this skill is for complex systems/decisions. Suggest a project update format instead; only use this skill if there’s a systemic pattern to diagnose.